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The tremendous growth of wireless applications and the demand for high data rate, the spectrum utilization improvement has been the most crucial challenges for wireless communication. Adapting cognitive radio with orthogonal frequency division multiplexing or offset quadrature amplitude modulation (OFDM/OQAM) improves the spectrum and energy efficiencies.

Thus, it overcomes the spectral leakage problem at the transmitter side and leads to less interference from secondary user (SUs) to primary user (PUs) and between the SUs in cognitive radio technology. The benefit of exploiting pulse shape filtering in the OFDM/OQAM is to not only eliminate the requirement of the guard bands but also reduce the out of band energy transmission, which also improves the spectral isolation from the neighboring systems. But the high peak to average power ratio (PAPR) phenomenon is a common issue in the majority of the multicarrier modulation systems and thus OFDM/OQAM is no exception in this case.

Therefore, this paper aims to examine the effect of integrating the Walsh–Hadamard Transform (WHT) on the power spectral density and investigates the problem of PAPR in the WHT/OQAM system.

Thus, it overcomes the spectral leakage problem at the transmitter side and leads to less interference from SUs to PUs and between the SUs in cognitive radio technology. The benefit of exploiting pulse shape filtering in the OFDM/OQAM is to not only eliminate the requirement of the guard bands but also reduce the out of band energy transmission, which also improves the spectral isolation from the neighboring systems. But the high PAPR phenomenon is a common issue in the majority of the multicarrier modulation systems thus OFDM/OQAM is no exception in this case.

The purpose of this paper is to find the approximate solutions of unsteady squeezing nanofluid flow and heat transfer between two parallel plates in the presence of variable heat source, viscous dissipation and inclined magnetic field using collocation method (CM).

The partial governing equations are reduced to nonlinear ordinary differential equations by using appropriate transformations and then are solved analytically by using the CM.

It is observed that the enhancing values of aligned angle of the magnetic causes a reduction in temperature distribution. It is also seen that the effect of nanoparticle volume fraction is significant on the temperature but negligible on the velocity profile.

To the best of the authors’ knowledge, no research has been carried out considering the combined effects of inclined Lorentz forces and variable heat source on squeezing flow and heat transfer of nanofluid between the infinite parallel plates.

A central goal of strategic management is to understand why some organizations outperform others. Based on the literature, we test the links among strategic resources, firm’s strategic orientation, and performance using data from 1,201 Spanish small and medium‐sized enterprises. The results can guide managers to invest in the appropriate resources since there is evidence that technology, innovation, quality, and human resource management leads to better company performance. It is also shown how strategic resources varies according to strategic orientation.

The purpose of this paper is to enhance the accuracy of classification of streaming big data sets with lesser processing time. This kind of social analytics would contribute to society with inferred decisions at a correct time. The work is intended for streaming nature of Twitter data sets.

It is a demanding task to analyse the increasing Twitter data by the conventional methods. The MapReduce (MR) is used for quickest analytics. The online feature selection (OFS) accelerated bat algorithm (ABA) and ensemble incremental deep multiple layer perceptron (EIDMLP) classifier is proposed for Feature Selection and classification. Three Twitter data sets under varied categories are investigated (product, service and emotions). The proposed model is compared with Particle Swarm Optimization, Accelerated Particle Swarm Optimization, accelerated simulated annealing and mutation operator (ASAMO). Feature Selection algorithms and classifiers such as Naïve Bayes, support vector machine, Hoeffding tree and fuzzy minimal consistent class subset coverage with the k-nearest neighbour (FMCCSC-KNN).

The proposed model is compared with PSO, APSO, ASAMO. Feature Selection algorithms, and classifiers such as Naïve Bayes (NB), support vector machine (SVM), Hoeffding Tree (HT), and Fuzzy Minimal Consistent Class Subset Coverage with the K-Nearest Neighbour (FMCCSC-KNN). The outcome of the work has achieved an accuracy of 99%, 99.48%, 98.9% for the given data sets with the processing time of 0.0034, 0.0024, 0.0053, seconds respectively.

A novel framework is proposed for Feature Selection and classification. The work is compared with the authors’ previously developed classifiers with other state-of-the-art Feature Selection and classification algorithms.

The purpose of this paper is the physico-chemical, microbiological, colorimetric, sensorial characterization of choris, a traditional smoked pork sausage produced in the state of Goa (India), including its storage stability (0–180 days) at room temperature, aiming at the geographical indication certification and entrepreneurship prospects.

A total of 48 samples of “choris” were collected from 24 villages of Goa and were analyzed at different intervals (0–180 days) for physico-chemical, proximate, microbiological, colorimetric and sensory attributes during the storage at room temperature.

The mean pH of 4.45 and water activity (a_w) of 0.78 were recorded. The pH, tyrosine value, fat percentage and free fatty acid content registered a significant increase, whereas moisture content, a_w and moisture–protein ratio reduced as storage progresses. The colorimetric values lightness (L*), hue angle (H*) and redness index values reduced significantly during storage. The mean total viable count, yeast and mold, and lactic acid bacteria count were found to proliferate significantly as storage advanced. Nevertheless, the hedonic scores not reaching an unacceptable level (= 4) at the end of the storage period.

In accordance with the various parameters adopted during the study, choris could be characterized as “naturally fermented dry smoked” sausages, which were shelf-stable at room temperature for 180 days. The product characterization of choris is essential to guarantee the genuineness, safety and consumer's acceptability. This study will also rebound in an augmented uniformity of the product, which will favor the geographical indication certification and the entrepreneurship prospects of this traditional product.

This study aims to assign efficiency score and then ranking the Indian companies known for best practices to control carbon-emission in the environment. It is destined to benchmark one company for best performance on the basis of selected alternatives among its peer group companies.

The present study has used a hybrid model by applying data envelopment analysis (DEA)-technique for order performance by similarity to ideal solution (TOPSIS) to measure the efficiency and ranking of various decision units on the basis of specified variables.

The findings of DEA have given the best alternative or best decision-making unit (DMU) among the set of 25 DMUs considered for empirical testing. The DEA technique is used with TOPSIS, which is another popular multi-criteria decision model. The integrated DEA-TOPSIS model has helped to compute the efficiency score of all 25 DMUs of study and also provide a unique rank to each of the efficient unit identified with the help of DEA technique.

The findings of the study have provided Benchmark Company amongst the companies following best practices for saving energy and having best operating profits too. This benchmark business unit can be studied extensively by peer group companies to compare various parameters affecting their efficiency and profits both.

The findings of the study will promote the socially responsible practices by corporate citizens and adopt the practices to reduce their carbon footprints. It will also suggest to socially responsible investors to select the benchmark and most efficient companies for investment purpose.

The study is original in terms of measuring efficiency and ranking of companies known for best practices for controlling their carbon footprints and suggesting a benchmark company to its peer group. Also, the integrated approach of using DEA-TOPSIS for such type of studies also makes it distinctive from earlier work done in the related field.

The most widely recycled plastic in the world is recycled polyethylene terephthalate (rPET). To minimize the environmental related issues associated with synthetic fibers, several researchers have explored the potential use of recycled polyester fibers in developing various technical textile products. This study aims to develop needle-punched nonwoven fabrics from recycled polyester fibers and investigate its suitability in oil spill cleanup process.

According to Box and Behnken factorial design, 15 different needle-punched nonwoven fabrics from recycled polyester fibers were prepared by changing the parameters, namely, needle punch density, needle penetration depth and fabric areal weight. Several featured parameters such as oil sorption, oil retention, oil sorption kinetics, wettability and reusability performance were systematically elucidated.

The maximum oil sorption of recycled nonwoven polyester is found to be 24.85 g/g and 20.58 g/g for crude oil and vegetable oil, respectively. The oil retention is about 93%–96% in case of crude oil, whereas 87%–91% in case of vegetable oil. Recycled polyester nonwoven possesses good hydrophobic–oleophilic properties with static contact angle of 138° against water, whereas 0° against crude oil and vegetable oil. The reusability test results indicate that recycled polyester nonwoven fabric can be used several times because of its reusability features.

There is no detailed study on the oil sorption features of needle-punched nonwoven fabrics developed from recycled polyester fibers. This study is expected to help in developing fabrics for oil spill cleanups.

Sources highlight that insufficient skills of site supervisors considerably influence the progress of many construction projects in numerous countries. This study intends to identify the crucial supervisory competencies that influence the effectiveness of building project operations in the context of developing countries.

The crucial construction site supervisory competencies were qualitatively identified through a comprehensive literature survey and a series of expert interviews with the use of thematic analysis approaches. A questionnaire survey was then carried out among 154 building project firms to quantify the impacts of the competencies on the effectiveness of project tasks with the use of the relative importance index approach. Additionally, industry-consultative meetings were held using problem-focused communication strategies to scrutinise the necessary actions.

Overall, 22 cognitive elements and 24 skills/abilities of supervisors were determined as being critical according to their impact values, where the site supervisors cognitive domains in construction planning and construction materials were determined as the top-ranking competencies in the list, with their manual skills/abilities in labour management and labour performance evaluation. Accordingly, a group of key competency outcomes were produced for the considerations in developing new site supervisory training components. Relevant statistical analysis results and the industry consultative outcomes substantiated the validity and dependability of the overall results.

Although the study's focus was to site supervision procedures used in Sri Lankan building construction projects, the overall findings/outcomes might be put to the test in related situations in other emerging industries in other countries.

The study has constructed a base that shows how the significant site supervisory competencies influence the effectiveness of building construction operations, contributing to making a big difference in the methods of reskilling/upskilling in the industry associated with construction labour, supervision, efficiency management and productivity enhancement.

Past studies highlight a wide range of labour-related problems resulting in productivity loss in the construction industry of many developing countries. This study aims to quantify the impacts of labour-related factors on the productivity of construction operations in Sri Lankan building projects based on the viewpoint of engineers and construction managers for upgrading management/organisational policies and practices.

Qualitative and quantitative approaches were used to identify the critical factors. Further, a series of industry consultative discussions were conducted through problem-based communication approaches to analyse the actions required.

A total of 21 factors were determined as critical, where skills shortage, labourers’ thinking abilities, work experience, knowledge in construction works and discipline were leading in the list. The statistical tests and the experts’ discussion outcomes ensured the validity and reliability of the study findings.

The study outcomes will contribute to finding out better ways for directing labour in the industry practices and revising organisational policies towards achieving higher productivity levels in construction operations. Though the study findings are limited to the Sri Lankan context, some findings may be tested in other developing countries in similar scenarios.

The study findings show why the identified factors are critical, how those influence construction practices and what actions need to be considered for addressing the industry’s productivity-related challenges. These can play a key role in upgrading the construction management practices and organisational policies to the near-future stages.